Share
Energy Efficient Computation Offloading in Mobile Edge Computing (in English)
Ying Chen
(Author)
·
Ning Zhang
(Author)
·
Yuan Wu
(Author)
·
Springer
· Hardcover
Energy Efficient Computation Offloading in Mobile Edge Computing (in English) - Chen, Ying ; Zhang, Ning ; Wu, Yuan
$ 161.04
$ 169.99
You save: $ 8.95
Choose the list to add your product or create one New List
✓ Product added successfully to the Wishlist.
Go to My WishlistsIt will be shipped from our warehouse between
Monday, June 10 and
Tuesday, June 11.
You will receive it anywhere in United States between 1 and 3 business days after shipment.
Synopsis "Energy Efficient Computation Offloading in Mobile Edge Computing (in English)"
This book provides a comprehensive review and in-depth discussion of the state-of-the-art research literature and propose energy-efficient computation offloading and resources management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling and resource scheduling. Since the task arrival process and channel conditions are stochastic and dynamic, the authors first propose an energy efficient dynamic computing offloading scheme to minimize energy consumption and guarantee end devices' delay performance. To further improve energy efficiency combined with tail energy, the authors present a computation offloading and frequency scaling scheme to jointly deal with the stochastic task allocation and CPU-cycle frequency scaling for minimal energy consumption while guaranteeing the system stability. They also investigate delay-aware and energy-efficient computation offloading in a dynamic MEC system with multiple edge servers, and introduce an end-to-end deep reinforcement learning (DRL) approach to select the best edge server for offloading and allocate the optimal computational resource such that the expected long-term utility is maximized. Finally, the authors study the multi-task computation offloading in multi-access MEC via non-orthogonal multiple access (NOMA) and accounting for the time-varying channel conditions. An online algorithm based on DRL is proposed to efficiently learn the near-optimal offloading solutions.Researchers working in mobile edge computing, task offloading and resource management, as well as advanced level students in electrical and computer engineering, telecommunications, computer science or other related disciplines will find this book useful as a reference. Professionals working within these related fields will also benefit from this book.
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
- 0% (0)
All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
✓ Producto agregado correctamente al carro, Ir a Pagar.
